Collaborative Research: Enhancing Data Science and Statistics Teacher Education--Transforming and Building Community

Eastern Michigan University, Ypsilanti MI

Investigators

Abstract

This project aims to serve the national interest by building a community that will transform undergraduate teacher preparation so that future K-12 mathematics teachers are prepared to effectively teach modern data science and statistics (DS&S). Society demands that citizens be statistically and data literate, resulting in growing efforts at the secondary level to include more DS&S in the curriculum. To meet these demands, new teachers will need additional preparation to foster students’ statistical and data literacy. Secondary mathematics teacher education programs often minimally address DS&S in comparison to other branches of mathematics, and new teachers tend to lack content knowledge and confidence to teach statistics topics. Transformative activities of this project focus on modifications of curriculum within courses and programs, innovations to technological tools, and faculty development at a broad range of institutions. The project aims to examine the current state of DS&S teacher education and intends to assemble an extensive community of faculty, organizations, initiatives, and projects focused on transforming undergraduate teacher preparation in DS&S education. The challenge of transforming teacher preparation programs to integrate DS&S is met using tools, methods, and approaches of improvement science as a guiding theory of change. There are three specific project goals: A) investigate the current systems in undergraduate teacher preparation for teaching DS&S by examining early career mathematics teachers through surveys and classroom observations, and a second survey and interview study to identify problems of practice for DS&S of mathematics teacher education programs; B) build and sustain a DS&S teacher education networked improvement community through partnerships with national organizations and projects and extensive faculty learning opportunities; and C) reach a broad, large, and diverse teacher education audience through developing, curating and disseminating high quality DS&S teacher education curriculum materials. The Common Online Data Analysis Platform (CODAP) of the Concord Consortium, “an easy¬-to-¬use data analysis environment designed for grades 5 through 14,” is the primary technology to be used in engaging with data, simulation and modeling. In this project, CODAP functionality is to be expanded and capabilities modified. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities. Partial funding is from the Robert Noyce Teacher Scholarship program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.